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1.
André St‐Hilaire Taha B. M. J. Ouarda Zoubeida Bargaoui Anik Daigle Laurent Bilodeau 《水文研究》2012,26(9):1302-1310
Water temperature is a key abiotic variable that modulates both water chemistry and aquatic life in rivers and streams. For this reason, numerous water temperature models have been developed in recent years. In this paper, a k‐nearest neighbour model (KNN) is proposed and validated to simulate and eventually produce a one‐day forecast of mean water temperature on the Moisie River, a watercourse with an important salmon population in eastern Canada. Numerous KNN model configurations were compared by selecting different attributes and testing different weight combinations for neighbours. It was found that the best model uses attributes that include water temperature from the two previous days and an indicator of seasonality (day of the year) to select nearest neighbours. Three neighbours were used to calculate the estimated temperature, and the weighting combination that yielded the best results was an equal weight on all three nearest neighbours. This nonparametric model provided lower Root Mean Square Errors (RMSE = 1·57 °C), Higher Nash coefficient (NTD = 0·93) and lower Relative Bias (RB = ? 1·5%) than a nonlinear regression model (RMSE = 2·45 °C, NTD = 0·83, RB = ? 3%). The k‐nearest neighbour model appears to be a promising tool to simulate of forecast water temperature where long time series are available. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
2.
Stream temperature modelling using artificial neural networks: application on Catamaran Brook,New Brunswick,Canada 总被引：2，自引：0，他引：2
Fish habitat and aquatic life in rivers are highly dependent on water temperature. Therefore, it is important to understand andto be able to predict river water temperatures using models. Such models can increase our knowledge of river thermal regimes as well as provide tools for environmental impact assessments. In this study, artificial neural networks (ANNs) will be used to develop models for predicting both the mean and maximum daily water temperature. The study was conducted within Catamaran Brook, a small drainage basin tributary to the Miramichi River (New Brunswick, Canada). In total, eight ANN models were investigated using a variety of input parameters. Of these models, four predicted mean daily water temperature and four predicted maximum daily water temperature. The best model for mean daily temperature had eight input parameters: minimum, maximum and mean air temperatures of the current day and those of the preceding day, the day of year and the water level. This model had an overall root‐mean‐square error (RMSE) of 0·96 °C, a bias of 0·26 °C and a coefficient of determination R2 = 0·971. The model that best predicted maximum daily water temperature was similar to the first model but excluded mean daily air temperature. Good results were obtained for maximum water temperatures with an overall RMSE of 1·18 °C, a bias of 0·15 °C and R2 = 0·961. The results of ANN models were similar to and/or better than those observed from the literature. The advantages of artificial neural networks models in modelling river water temperature lie in their simplicity of use, their low data requirement and their good performance, as well as their flexibility in allowing many input and output parameters. Copyright © 2008 Crown in the right of Canada and John Wiley & Sons, Ltd. 相似文献
3.
Behrouz Ahmadi‐Nedushan André St‐Hilaire Taha B. M. J. Ouarda Laurent Bilodeau Élaine Robichaud Nathalie Thiémonge Bernard Bobée 《水文研究》2007,21(1):21-34
Successful applications of stochastic models for simulating and predicting daily stream temperature have been reported in the literature. These stochastic models have been generally tested on small rivers and have used only air temperature as an exogenous variable. This study investigates the stochastic modelling of daily mean stream water temperatures on the Moisie River, a relatively large unregulated river located in Québec, Canada. The objective of the study is to compare different stochastic approaches previously used on small streams to relate mean daily water temperatures to air temperatures and streamflow indices. Various stochastic approaches are used to model the water temperature residuals, representing short‐term variations, which were obtained by subtracting the seasonal components from water temperature time‐series. The first three models, a multiple regression, a second‐order autoregressive model, and a Box and Jenkins model, used only lagged air temperature residuals as exogenous variables. The root‐mean‐square error (RMSE) for these models varied between 0·53 and 1·70 °C and the second‐order autoregressive model provided the best results. A statistical methodology using best subsets regression is proposed to model the combined effect of discharge and air temperature on stream temperatures. Various streamflow indices were considered as additional independent variables, and models with different number of variables were tested. The results indicated that the best model included relative change in flow as the most important streamflow index. The RMSE for this model was of the order of 0·51 °C, which shows a small improvement over the first three models that did not include streamflow indices. The ridge regression was applied to this model to alleviate the potential statistical inadequacies associated with multicollinearity. The amplitude and sign of the ridge regression coefficients seem to be more in agreement with prior expectations (e.g. positive correlation between water temperature residuals of different lags) and make more physical sense. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献
4.
Water temperature influences most of the physical, chemical and biological properties of rivers. It plays an important role in the distribution of fish and the growth rates of many aquatic organisms. Therefore, a better understanding of the thermal regime of rivers is essential for the management of important fisheries resources. This study deals with the modelling of river water temperature using a new and simplified model based on the equilibrium temperature concept. The equilibrium temperature concept is an approach where the net heat flux at the water surface can be expressed by a simple equation with fewer meteorological parameters than required with traditional models. This new water temperature model was applied on two watercourses of different size and thermal characteristics, but within a similar meteorological region, i.e., the Little Southwest Miramichi River and Catamaran Brook (New Brunswick, Canada). A study of the long‐term thermal characteristics of these two rivers revealed that the greatest differences in water temperatures occurred during mid‐summer peak temperatures. Data from 1992 to 1994 were used for the model calibration, while data from 1995 to 1999 were used for the model validation. Results showed a slightly better agreement between observed and predicted water temperatures for Catamaran Brook during the calibration period, with a root‐mean‐square error (RMSE) of 1·10 °C (Nash coefficient, NTD = 0·95) compared to 1·45 °C for the Little Southwest Miramichi River (NTD = 0·94). During the validation period, RMSEs were calculated at 1·31 °C for Catamaran Brook and 1·55 °C for the Little Southwest Miramichi River. Poorer model performances were generally observed early in the season (e.g., spring) for both rivers due to the influence of snowmelt conditions, while late summer to autumn modelling performances showed better results. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
5.
Insights on stream temperature processes through development of a coupled hydrologic and stream temperature model for forested coastal headwater catchments 
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下载免费PDF全文 Stream temperature controls a number of biological, chemical, and physical processes occurring in aquatic environments. Transient snow cover and advection associated with lateral throughflow inputs can have a dominant influence on stream thermal regimes for headwater catchments in the rain‐on‐snow zone. Most existing stream temperature models lack the ability to properly simulate these processes. We developed and evaluated a conceptual‐parametric catchment‐scale stream temperature model that includes the role of transient snow cover and lateral advection associated with throughflow. The model consists of routines for simulating canopy interception, snow accumulation and melt, hillslope throughflow runoff and temperature, and stream channel energy exchange processes. The model was used to predict discharge and stream temperature for a small forested headwater catchment near Vancouver, Canada, using long‐term (1963–2013) weather data to compute model forcing variables. The model was evaluated against 4 years of observed stream temperature. The model generally predicted daily mean stream temperature accurately (annual RMSE between 0.57 and 1.24 °C) although it overpredicted daily summer stream temperatures by up to 3 °C during extended low streamflow conditions. Model development and testing provided insights on the roles of advection associated with lateral throughflow, channel interception of snow, and surface–subsurface water interactions on stream thermal regimes. This study shows that a relatively simple but process‐based model can provide reasonable stream temperature predictions for forested headwater catchments located in the rain‐on‐snow zone. 相似文献
6.
Continuous temperature measurements at 11 stream sites in small lowland streams of North Zealand, Denmark over a year showed much higher summer temperatures and lower winter temperatures along the course of the stream with artificial lakes than in the stream without lakes. The influence of lakes was even more prominent in the comparisons of colder lake inlets and warmer outlets and led to the decline of cold‐water and oxygen‐demanding brown trout. Seasonal and daily temperature variations were, as anticipated, dampened by forest cover, groundwater input, input from sewage plants and high downstream discharges. Seasonal variations in daily water temperature could be predicted with high accuracy at all sites by a linear air‐water regression model (r2: 0·903–0·947). The predictions improved in all instances (r2: 0·927–0·964) by a non‐linear logistic regression according to which water temperatures do not fall below freezing and they increase less steeply than air temperatures at high temperatures because of enhanced heat loss from the stream by evaporation and back radiation. The predictions improved slightly (r2: 0·933–0·969) by a multiple regression model which, in addition to air temperature as the main predictor, included solar radiation at un‐shaded sites, relative humidity, precipitation and discharge. Application of the non‐linear logistic model for a warming scenario of 4–5 °C higher air temperatures in Denmark in 2070‐2100 yielded predictions of temperatures rising 1·6–3·0 °C during winter and summer and 4·4–6·0 °C during spring in un‐shaded streams with low groundwater input. Groundwater‐fed springs are expected to follow the increase of mean air temperatures for the region. Great caution should be exercised in these temperature projections because global and regional climate scenarios remain open to discussion. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献
7.
River temperature models play an increasingly important role in the management of fisheries and aquatic resources. Among river temperature models, forecasting models remain relatively unused compared to water temperature simulation models. However, water temperature forecasting is extremely important for in-season management of fisheries, especially when short-term forecasts (a few days) are required. In this study, forecast and simulation models were applied to the Little Southwest Miramichi River (New Brunswick, Canada), where water temperatures can regularly exceed 25–29°C during summer, necessitating associated fisheries closures. Second- and third-order autoregressive models (AR2, AR3) were calibrated and validated using air temperature as the exogenous variable to predict minimum, mean and maximum daily water temperatures. These models were then used to predict river temperatures in forecast mode (1-, 2- and 3-day forecasts using real-time data) and in simulation mode (using only air temperature as input). The results showed that the models performed better when used to forecast rather than simulate water temperatures. The AR3 model slightly outperformed the AR2 in the forecasting mode, with root mean square errors (RMSE) generally between 0.87°C and 1.58°C. However, in the simulation mode, the AR2 slightly outperformed the AR3 model (1.25°C < RMSE < 1.90°C). One-day forecast models performed the best (RMSE ~ 1°C) and model performance decreased as time lag increased (RMSE close to 1.5°C after 3 days). The study showed that marked improvement in the modelling can be accomplished using forecasting models compared to water temperature simulations, especially for short-term forecasts.
EDITOR M.C. Acreman ASSOCIATE EDITOR S. Huang 相似文献
8.
Water temperature has a significant influence on aquatic organisms, including stenotherm fish such as salmonids. It is thus of prime importance to build reliable tools to forecast water temperature. This study evaluated a statistical scheme to model average water temperature based on daily average air temperature and average discharge at the Sainte-Marguerite River, Northern Canada. The aim was to test a non-parametric water temperature generalized additive model (GAM) and to compare its performance to three previously developed approaches: the logistic, residuals regression and linear regression models. Due to its flexibility, the GAM was able to capture some of the nonlinear response between water temperature and the two explanatory variables (air temperature and flow). The shape of these effects was determined by the trends shown in the collected data. The four models were evaluated annually using a cross-validation technique. Three comparison criteria were calculated: the root mean square error (RMSE), the bias error and the Nash-Sutcliffe coefficient of efficiency (NSC). The goodness of fit of the four models was also compared graphically. The GAM was the best among the four models (RMSE = 1.44°C, bias = ?0.04 and NSC = 0.94). 相似文献
9.
Hydrological modelling depends highly on the accuracy and uncertainty of model input parameters such as soil properties. Since most of these data are field surveyed, geostatistical techniques such as kriging, classification and regression trees or more sophisticated soil‐landscape models need to be applied to interpolate point information to the area. Most of the existing interpolation techniques require a random or regular distribution of points within the study area but are not adequate to satisfactorily interpolate soil catena or transect data. The soil landscape model presented in this study is predicting soil information from transect or catena point data using a statistical mean (arithmetic, geometric and harmonic mean) to calculate the soil information based on class means of merged spatial explanatory variables. A data set of 226 soil depth measurements covering a range of 0–6·5 m was used to test the model. The point data were sampled along four transects in the Stubbetorp catchment, SE‐Sweden. We overlaid a geomorphology map (8 classes) with digital elevation model‐derived topographic index maps (2–9 classes) to estimate the range of error the model produces with changing sample size and input maps. The accuracy of the soil depth predictions was estimated with the root mean square error (RMSE) based on a testing and training data set. RMSE ranged generally between 0·73 and 0·83 m ± 0·013 m depending on the amount of classes the merged layers had, but were smallest for a map combination with a low number of classes predicted with the harmonic mean (RMSE = 0·46 m). The results show that the prediction accuracy of this method depends on the number of point values in the sample, the value range of the measured attribute and the initial correlations between point values and explanatory variables, but suggests that the model approach is in general scale invariant. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
10.
Jason R. Janke 《地球表面变化过程与地形》2005,30(12):1495-1508
Rock glaciers, a feature associated with at least discontinuous permafrost, provide important topoclimatic information. Active and inactive rock glaciers can be used to model current permafrost distribution. Relict rock glacier locations provide paleoclimatic information to infer past conditions. Future warmer climates could cause permafrost zones to shrink and initiate slope instability hazards such as debris flows or rockslides, thus modeling change remains imperative. This research examines potential past and future permafrost distribution in the Colorado Front Range by calibrating an existing permafrost model using a standard adiabatic rate for mountains (0·5 °C per 100 m) for a 4 °C range of cooler and warmer temperatures. According to the model, permafrost currently covers about 12 per cent (326·1 km2) of the entire study area (2721·5 km2). In a 4 °C cooler climate 73·7 per cent (2004·4 km2) of the study area could be covered by permafrost, whereas in a 4°C warmer climate almost no permafrost would be found. Permafrost would be reduced severely by 93·9 per cent (a loss of 306·2 km2) in a 2·0 °C warmer climate; however, permafrost will likely respond slowly to change. Relict rock glacier distribution indicates that mean annual air temperature (MAAT) was once at least some 3·0 to 4·0 °C cooler during the Pleistocene, with permafrost extending some 600–700 m lower than today. The model is effective at identifying temperature sensitive areas for future monitoring; however, other feedback mechanisms such as precipitation are neglected. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
11.
K. P. Paaijmans A. F. G. Jacobs W. Takken B. G. Heusinkveld A. K. Githeko M. Dicke A. A. M. Holtslag 《水文研究》2008,22(24):4789-4801
Water temperature is an important determinant of the growth and development of malaria mosquito immatures. To gain a better understanding of the daily temperature dynamics of malaria mosquito breeding sites and of the relationships between meteorological variables and water temperature, three clear water pools (diameter × depth: 0·16 × 0·04, 0·32 × 0·16 and 0·96 × 0·32 m) were created in Kenya. Continuous water temperature measurements at various depths were combined with weather data collections from a meteorological station. The water pools were homothermic, but the top water layer differed by up to about 2 °C in temperature, depending on weather conditions. Although the daily mean temperature of all water pools was similar (27·4–28·1 °C), the average recorded difference between the daily minimum and maximum temperature was 14·4 °C in the smallest versus 7·1 °C in the largest water pool. Average water temperature corresponded well with various meteorological variables. The temperature of each water pool was continuously higher than the air temperature. A model was developed that predicts the diurnal water temperature dynamics accurately, based on the estimated energy budget components of these water pools. The air–water interface appeared the most important boundary for energy exchange processes and on average 82–89% of the total energy was gained and lost at this boundary. Besides energy loss to longwave radiation, loss due to evaporation was high; the average estimated daily evaporation ranged from 4·2 mm in the smallest to 3·7 mm in the largest water pool. Copyright © 2008 John Wiley & Sons, Ltd. 相似文献
12.
A cell‐based long‐term hydrological model (CELTHYM) that can be integrated with a geographical information system (GIS) was developed to predict continuous stream flow from small agricultural watersheds. The CELTHYM uses a cell‐by‐cell soil moisture balance approach. For surface runoff estimation, the curve number technique considering soil moisture on a daily basis was used, and release rate was used to estimate baseflow. Evapotranspiration was computed using the FAO modified Penman equation that considered land‐use‐based crop coefficients, soil moisture and the influence of topography on radiation. A rice paddy field water budget model was also adapted for the specific application of the model to East Asia. Model sensitivity analysis was conducted to obtain operational information about the model calibration parameters. The CELTHYM was calibrated and verified with measured runoff data from the WS#1 and WS#3 watersheds of the Seoul National University, Department of Agricultural Engineering, in Hwaseong County, Kyounggi Province, South Korea. The WS#1 watershed is comprised of about 35·4% rice paddy fields and 42·3% forest, whereas the WS#3 watershed is about 85·0% forest and 11·5% rice paddy fields. The CELTHYM was calibrated for the parameter release rate, K, and soil moisture storage coefficient, STC, and results were compared with the measured runoff data for 1986. The validation results for WS#1 considering all daily stream flow were poor with R2, E2 and RMSE having values of 0·40, ?6·63 and 9·69 (mm), respectively, but validation results for days without rainfall were statistically significant (R2 = 0·66). Results for WS#3 showed good agreement with observed data for all days, and R2, E2 and RMSE were 0·92, 0·91 and 2·23 (mm), respectively, suggesting potential for CELTHYM application to other watersheds. The direct runoff and water balance components for watershed WS#1 with significant areas of paddy fields did not perform well, suggesting that additional study of these components is needed. Copyright © 2002 John Wiley & Sons, Ltd. 相似文献
13.
Thermochron iButtons incorporate the latest in digital technology, making them smaller, less expensive, durable and potentially more reliable than many other temperature logging devices. The objective of this study was to test the accuracy of an inexpensive air temperature measurement system, composed of a Thermochron iButton and radiation shield. Sixty‐one iButtons were subjected to a sequence of two water baths (0 °C and 24·9 °C) to assess the absolute accuracy of the sensors. Five solar radiation shields were tested in a greenhouse setting to evaluate the reduction in radiative heating. Significant differences (p < 0·05) were detected between instruments subsequent to both water‐bath treatment analyses. The accuracy of the sensors was well within the manufacturer's stated specification of ±1·0 °C with a collective temperature variance of ±0·21 °C. Temperature responses generated by the Thermochron iButtons in different radiation shields were consistent, but varied significantly (p < 0·05) from 28 to 44 °C based on diurnal temperature ranges. Results indicate that the Thermochron iButton is an accurate, inexpensive alternative to more expensive temperature data‐logging systems, and is well suited for obtaining quality spatially distributed data for hydrologic and water quality investigations. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
14.
Stream temperature ranged from 3 to 4°C at an experimental site during snowmelt on Hokkaido Island, Japan, which provided direct evidence of major contributions of subsurface water to stream water. In contrast, stream temperatures during rainstorms in summer decreased gradually after stream flow peaked, attaining a nearly constant temperature ranging from 9 to 11°C. During storm flow recession, stream temperatures during summer or snowmelt were similar to the soil temperature at 1·8 m below the land surface, suggesting that subsurface water contributions to stream flow are derived from this depth. The hygrographs during two rainstorms, August 1987 and September 1989, were separated using temperature. The stream temperature was assumed to depend on the mixing of surface flow, having a temperature ranging from that of rainfall to that of shallow (50 cm deep) soil water, and subsurface flow, having the temperature of the soil at 1·8 m below the land surface. Subsurface flow was estimated to contribute 85–90% of the total stream flow during each rainstorm. A two‐component hydrograph separation was also evaluated using specific conductance. Runoff contributions from the two sources for the temperature and specific conductance analysis were similar. Analysis of the temperature and conductance–discharge hysteresis loop, and of individual flow components for storm hygrographs, provide a general picture of the runoff process in the experimental basin. Copyright © 1999 John Wiley & Sons, Ltd. 相似文献
15.
Stream temperature, an important measure of ecosystem health, is expected to be altered by future changes in climate and land use, potentially leading to shifts in habitat distribution for aquatic organisms dependent on particular temperature regimes. To assess the sensitivity of stream temperature to change in a region where such a shift has the potential to occur, we examine the variability of and controls on the direct relationship between air and water temperature across the state of Pennsylvania. We characterized the relationship between air and stream temperature via linear and nonlinear regression for 57 sites across Pennsylvania at daily and weekly timescales. Model fit (r2) improved for 92% (daily) and 65% (weekly) of sites for nonlinear versus linear relationships. Fit for weekly versus daily regression analysis improved by 0·08 for linear and 0·06 for nonlinear regression relationships. To investigate the mechanisms controlling stream temperature sensitivity to environmental change, we define ‘thermal sensitivity’ as the sensitivity of stream temperature of a given site to change in air temperature, quantified as the slope of the regression line between air and stream temperature. Air temperature accounted for 60–95% of the daily variation in stream temperature for sites at or above a Strahler stream order (SO) of 3, with thermal sensitivities ranging from low (0·02) to high (0·93). The sensitivity of stream temperature to air temperature is primarily controlled by stream size (SO) and baseflow contribution. Together, SO and baseflow index explained 43% of the variance in thermal sensitivity across the state, and 59% within the Susquehanna River Basin. In small streams, baseflow contribution was the major determinant of thermal sensitivity, with increasing baseflow contributions resulting in decreasing sensitivity values. In large streams, thermal sensitivity increased with stream size, as a function of accumulated heat throughout the stream network. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
16.
A physics‐based model is provided for predicting the impact of climate change on stream temperature and, in turn, on Formosan landlocked salmon (Oncorhynchus masou formosanus) habitat. Because upstream watersheds on Taiwan Island are surrounded with high and steep mountains, the influence of mountain shading on solar radiation and longwave radiation is taken into account by using a digital elevation model. Projections using CGCM2 and HADCM3 models and CCCM and GISS models provided information on future climatic conditions. The results indicate that annual average stream temperatures may rise by 0·5 °C (HADCM3 short term) to 2·9 °C (CGCM2 long term) due to climate change. The simulation results also indicate that the average suitable habitat for the Formosan landlocked salmon may decline by 333 m (HADCM3 short term) to 1633 m (CGCM2 long term) and 166 m (HADCM3 short term) to 1833 m (CGCM2 long term) depending on which thermal criterion (17 °C and 18 °C respectively) is applied. The results of this study draw attention to the tasks of Formosan landlocked salmon conservation agencies, not only with regard to restoration plans of the local environment, but also to the mitigation strategies to global climate change that are necessary and require further research. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
17.
The active layer of frozen ground data assimilation system adopts the SHAW (Simulteneous Heat and Water) model as the model
operator. It employs an ensemble kalman filter to fuse state variables predicted by the SHAW model with in situ observation and the SSM/I 19 GHz brightness temperature for the purpose of optimizing model hydrothermal state variables.
When there is little water movement in the frozen soil during the winter season, the unfrozen water content depends primarily
on soil temperature. Thus, soil temperature is the crucial state variable to be improved. In contrast, soil moisture is heavily
influenced by precipitation during the summer season. The simulation accuracy of soil moisture has a strong and direct impact
on the soil temperature. In this case, the crucial state variable to be improved is soil moisture. One-dimensional assimilation
experiments that have been carried out at AMDO station show that land data assimilation method can improve the estimation
of hydrothermal state variables in the soil by fusing model information and observation information. The reasonable model
error covariance matrix plays a key role in transferring the optimized surface state information to the deep soil, and it
provides improved estimations of whole soil state profiles. After assimilating the 4-cm soil temperature by in situ observation, the soil temperature RMSE (Root Mean Square Error) of each soil layer decreased by 0.96°C on average relative
to the SHAW simulation. After assimilating the 4-cm soil moisture in situ observation, the soil moisture RMSE of each soil layer decreased by 0.020 m3·m−3. When assimilating the SSM/I 19 GHz brightness temperature, the soil temperature RMSE of each soil layer during the winter
decreased by 0.76°C, while the soil moisture RMSE of each soil layer during the summer decreased by 0.018 m3·m−3. 相似文献
18.
19.
Stream temperature is a critical water quality parameter that is not fully understood, particularly in urban areas. This study explores drivers contributing to stream temperature variability within an urban system, at 21 sites within the Philadelphia region, Pennsylvania, USA. A comprehensive set of temperature metrics were evaluated, including temperature sensitivity, daily maximum temperatures, time >20°C, and temperature surges during storms. Wastewater treatment plants (WWTPs) were the strongest driver of downstream temperature variability along 32 km in Wissahickon Creek. WWTP effluent temperature controlled local (1–3 km downstream) temperatures year-round, but the impacts varied seasonally: during winter, local warming of 2–7°C was consistently observed, while local cooling up to 1°C occurred during summer. Summer cooling and winter warming were detected up to 12 km downstream of a WWTP. Comparing effects from different WWTPs provided guidelines for mitigating their thermal impact; WWTPs that discharged into larger streams, had cooler effluent, or had lower discharge had less effect on stream temperatures. Comparing thermal regimes in four urban headwater streams, sites with more local riparian canopy had cooler maximum temperatures by up to 1.5°C, had lower temperature sensitivity, and spent less time at high temperatures, although mean temperatures were unaffected. Watershed-scale impervious area was associated with increased surge frequency and magnitude at headwater sites, but most storms did not result in a surge and most surges had a low magnitude. These results suggest that maintaining or restoring riparian canopy in urban settings will have a larger impact on stream temperatures than stormwater management that treats impervious area. Mitigation efforts may be most impactful at urban headwater sites, which are particularly vulnerable to stream temperature disruptions. It is vital that stream temperature impacts are considered when planning stormwater management or stream restoration projects, and the appropriate metrics need to be considered when assessing impacts. 相似文献
20.
Changes in stream water quality due to logging of the boreal forest in the Montmorency Forest,Québec
Yohann Tremblay Alain N. Rousseau André P. Plamondon Denis Lévesque Marcel Prévost 《水文研究》2009,23(5):764-776
Summer stream water quality was monitored before and following the logging of 50% of the boreal forest within three small watersheds (<50 ha) nested in the ‘Ruisseau des Eaux‐Volées’ Experimental Watershed, Montmorency Forest (Québec, Canada). Logging was conducted in winter, on snow cover according to recommended best management practices (BMPs) to minimize soil disturbance and protect advance growth. A 20‐m forest buffer was maintained along perennial streams. In watershed 7·2, cut‐blocks were located near the stream network and logging was partially allowed within the riparian buffer zone. In watersheds 7·5 and 7·7, logging occurred farther away from the stream network. Observations were also made for watershed 7·3 that collected the runoff from watersheds 7·2 and 7·5, and watershed 7·6, the uproad portion of watershed 7·7. The control watershed 0·2 was contiguous to the impacted watersheds and remained undisturbed. Following clearcutting, changes in summer daily maximum and minimum stream temperatures remained within ± 1 °C while changes in diurnal variation did not decrease by more than 0·5 °C. Concentrations of NO3? greatly increased by up to 6000% and concentrations of K+ increased by up to 300% during the second summer after logging. Smaller increases were observed for Fetotal (up to 71%), specific conductance (up to 26%), and Mg2+ (up to 19%). Post‐logging pH decreased slightly by no more than 7% while PO43? concentration remained relatively constant. Suspended sediment concentrations appeared to increase during post‐logging, but there was not enough pre‐logging data to statistically confirm this result. Logging of moderate intensity and respecting established BMPs may account for the limited changes of water quality parameters and the low exceedances of the criteria for the protection of aquatic life. The proximity of the cutover to the stream network and logging within the riparian zone did not appear to affect water quality. Copyright © 2008 John Wiley & Sons, Ltd. 相似文献